Detecting Minor Symptoms of Parkinson's Disease in the Wild Using Bi-LSTM with Attention Mechanism.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor and nonmotor impairment with various implications on patients' quality of life. Since currently available therapies are only symptomatic, identifying individuals with prodromal, preclinical, or early-stage PD is crucial, as they would be ideal candidates for future disease-modifying therapies. Our analysis aims to develop a robust model for accurate PD detection using accelerometer data collected from PD and non-PD individuals with mild or no tremor during phone conversations. An open-access dataset comprising accelerometer recordings from 22 PD patients and 11 healthy controls (HCs) was utilized. The data were preprocessed to extract relevant time-, frequency-, and energy-related features, and a bidirectional long short-term memory (Bi-LSTM) model with attention mechanism was employed for classification. The performance of the model was evaluated using fivefold cross-validation, and metrics of accuracy, precision, recall, specificity, and f1-score were computed. The proposed model demonstrated high accuracy (98%), precision (99%), recall (98%), specificity (96%), and f1-score (98%) in accurately distinguishing PD patients from HCs. Our findings indicate that the proposed model outperforms existing approaches and holds promise for detection of PD with subtle symptoms, like tremor, in the wild. Such symptoms can present in the early or even prodromal stage of the disease, and appropriate mobile-based applications may be a practical tool in real-life settings to alert individuals at risk to seek medical assistance or give patients feedback in monitoring their symptoms.

Identification of a novel de novo KMT2B variant in a Greek dystonia patient via exome sequencing genotype-phenotype correlations of all published cases.

Mutations in Lysine-Specific Histone Methyltransferase 2B gene (KMT2B) have been reported to be associated with isolated and complex early-onset generalized dystonia. We describe clinico-genetic features on a Greek patient with a novel de novo variant and demonstrate the phenotypic spectrum of KMT2B variants. We performed whole exome sequencing (WES), in a Greek patient with sporadic generalized dystonia. Additionally, we performed a systematic review of all published cases with KMT2B variants. The patient presented with isolated and mild generalized dystonia. We identified a novel splice site variant that was confirmed by Sanger sequencing and was not found in parents. This is the first reported KMT2B variant, in the Greek population. This case report further highlights the growing trend of identifying genetic diseases previously restricted to few cases in many different ethnic groups worldwide via exome sequencing. In the systematic review, we evaluated the mutation pathogenicity in all previously reported cases to investigate possible phenotype-genotype correlations. Greater mutation numbers in different populations will be important and mutation-specific functional studies will be essential to identify the pathogenicity of the various KMT2B variants.